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Parameter: Journal of Statistics
Published by Universitas Tadulako
ISSN : -     EISSN : 27765660     DOI : https://doi.org/10.22487/27765660.2021.v1.i2
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 38 Documents
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Application Biplot Analysis on Mapping of Non-Convertive Diseases in Indonesia Kris Suryowati; Maria Titah JP; Nurzaidah Nasution
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.713 KB) | DOI: 10.22487/27765660.2021.v1.i2.15518

Abstract

Non-communicable diseases is diseases that are not caused by germs but rather because of physiological or metabolic problems in human body tissues. Usually, this disease occurs due to unhealthy lifestyle. One way to find out how large the spread of non-communicable diseases is by mapping the disease using biplot analysis. Biplot analysis is applied to determine the proximity information between objects, the length of the change vector, the correlation between modifiers, and the value of the change in an object. The study was conducted in 33 provinces with twelve non-communicable diseases. Descriptive analysis of twelve non-communicable diseases averaged the highest joint disease of 10.51 followed by hypertensive disease 8.85 and Stroke 6.42. While the lowest average disease is Heart Failure disease by 0.10 it is still open to research with other methods and also need to add supporting variables
Forecasting the Consumer Price Index in Yogyakarta by Using the Double Exponential Smoothing Method Syintya Febriyanti; Wahyu Aji Pradana; Juliana Saputra Muhammad; Edy Widodo
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15641

Abstract

The Consumer Price Index (CPI) is an indicator that is often used to measure the inflation rate in an area, or can be interpreted as a comparison between the prices of a commodity package from a group of goods or services consumed by households over a certain period time. The spread of COVID-19 throughout the world affects the economy in Indonesia, especially Yogyakarta. Forecasting CPI data during the COVID-19 pandemic has the benefit of being an illustration of data collection in the CPI of D.I Yogyakarta Province in the predicted period. This is useful as a comparison with the original data at the time of data collection and publication, as well as a consideration in making policies and improving the economy. Researchers use the Double Exponential Smoothing (DES) method to predict the CPI of Yogyakarta D.I Province, which aims to determine the best forecasting model and forecasting results. This method is rarely used in research on CPI data forecasting in Yogyakarta. The data in this study are monthly data from March 2020 to August 2021. The highest CPI in Yogyakarta occurred in August 2021 at 107.21 or 107.2, while the lowest CPI in Yogyakarta occurred in April 2020 at 105.15 or 105.2. The average CPI in Yogyakarta per month is 106.1. The Mean Absolute Percentage Error (MAPE) value obtained from the DES method is 0.1308443%, so that the accuracy of the model is 99.869%. Forecasting with the DES method is quite well used in forecasting the CPI data of Yogyakarta in September 2020 - November 2021. The results of CPI forecasting in Yogyakarta using the DES method were 107.2602, 107.3104, and 107.3606 from September-November.
K-Means Clustering for Grouping Indonesia Underdeveloped Regions in 2020 Based on Poverty Indicators Resti Wahyuni
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15675

Abstract

Poverty is still a problem in Indonesia, especially in underdeveloped areas. Underdeveloped areas are areas where the region and its people are less developed than other regions on a national scale. The classification of disadvantaged areas is determined by the president in the Presidential Regulation of the Republic of Indonesia Number 63 of 2020 concerning the Determination of Underdeveloped Regions of 2020-2024. Various policies need to be set by the government to overcome poverty in underdeveloped areas. Program planning strategies may be different for each region. Therefore, in order to achieve an optimal implementation of poverty alleviation programs, it is necessary to group the districts covered in underdeveloped areas in Indonesia based on poverty indicators. The data used is macro data from the characteristics of each region in disadvantaged areas obtained from regional publications in the figures for each district. From the results of the analysis of k means clustering formed three groups with different characteristics in each cluster. In cluster one, the focus of government policies is on employment and sanitation aspects, cluster two is on health, education, and employment aspects, cluster three is on all aspects because cluster three is the area with the highest percentage of poor people compared to the other two clusters. The high percentage of poor people is also followed by other poor aspects.
Individual and Contextual Factors Affecting DPT Immunization in Indonesia Resti Wahyuni; Titik Harsanti
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15677

Abstract

Nowadays, diphtheria cases always increase from year to year. Until now, no drug has been found to cure diphtheria, but there is the most effective way of prevention through immunization. It is known that diphtheria sufferers who don’t get immunizations increase every year. The purpose of this study is to determine the individual and contextual factors that influence the status of DPT immunization in Indonesia and its trends and to know the diversity between cities. The data used in this study are Susenas KOR and consumption and expenditure (KP) modules. The results of multilevel binary logistic regression analysis indicate that individual factors that influence the status of DPT immunization are residence classification, highest maternal education, ownership of immunization cards, birth order, and household poverty status. While the contextual are the ratio of posyandu to 100,000 population and PDRB. Characteristics of children aged 12-59 who do not get immunizations tend to live in rural areas, have mothers with the highest education in junior high school, don’t have immunization cards, who born late in households with many children, and come from poor households. Besides that, there is a diversity of characteristics between cities, which amounted to 22,19%.
Forecasting of the Amount of Rupiah Banknotes Flows in the East Region of Indonesia Using Circular Regression Jassinca Chrissma Audina; Rais; Lilies Handayani
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15681

Abstract

Money is a tool that can be used in exchanging goods and services in a certain area. Increasing and decreasing in the money supply excessively can have a negative impact on the economy. For this reason, in order to maintain financial system stability in Indonesia, it is necessary to conduct an analysis of the data on the amount of outflows of rupiah currency at each Bank Indonesia office. In this study, a relationship analysis will be carried out between the eastern region of Indonesia and the amount of outflows of Bank Indonesia banknotes during the 2016-2018 period using circular regression analysis. The results showed that 83.03% of the variation in the amount of outflows of BI banknotes could be explained by the circular regression model that was formed. In addition, in the process of forecasting data on the amount of outflows of BI banknotes in the eastern region of Indonesia for the 2019-2020 period, the time series forecasting method is used which is based on the use of analysis of the relationship pattern between the estimated variables and the time variable.
Analysis of Skin Disease Infection After the Palu Earthquake Using Binary Logistic Regression Selvia Anggun Wahyuni; Lilies Handayani; Muhammad Akriyaldi Masdin; Salmia
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15682

Abstract

The incidence of skin disease in Indonesia is still relatively high and is a significant problem. This is evidenced by the 2010 Indonesian Health Profile data which shows that skin and subcutaneous tissue diseases are the third rank of the 10 most common diseases among outpatients in hospitals throughout Indonesia. Skin disease is growing, as evidenced by data from the Indonesian Ministry of Health, the prevalence of skin disease throughout Indonesia in 2012 was 8.46%, then increased in 2013 by 9 %. Palu City is an area that has a high skin disease problem. According to the 2016 BPS of Palu City, skin diseases are among the top 10 diseases in Palu City with a total of 11,363 sufferers. The method used in this research is binary logistic regression. Based on the analysis that has been done, it can be concluded that the best model is formed as follows:. Based on the best model, it is found that the factors that influence the transmission of skin diseases after the Palu earthquake are genetic factors.
Clustering of Province in Indonesia Based on Aquaculture Productivity Using Average Linkage Method Fachruddin Hari Anggara Putera; Septina F. Mangitung; Madinawati; Lilies Handayani
Parameter: Journal of Statistics Vol. 2 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2021.v2.i1.15683

Abstract

Fisheries are one of the agricultural sub-sectors that play an important role in contributing to income figures for the state and the region because most of Indonesia's territory is water so that the fisheries sector is a sub-sector that is feasible to be developed in this country, one of which is through aquaculture. One of the efforts that can increase and maintain productivity in the aquaculture sector is to classify provinces that produce aquaculture production into groups based on the similarity of characteristics possessed by each province in Indonesia. In this study, clustering was carried out using cluster analysis using the average linkage method and based on the analysis results obtained showed that cluster 1 consists of 25 provinces, cluster 2 consists of 5 provinces, cluster 3 consists of 2 provinces, cluster 4 consists of 1 province, and cluster 5 consists of 1 province with a standard deviation value within a cluster of 11,729 and a standard deviation between clusters of 118,745.
The Motivation of Criminality During the Covid-19 Pandemic in Central Sulawesi Fadjryani; Wawan Saputra
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15680

Abstract

With the news of the crime were often pushed in a variety of digital platforms and non- digital and criminal acts that are still happening in the community, make this topic endlessly to be discussed. Moreover, during the current pandemic, so many demands for life are not in line with the situation as a result of the implementation of the lockdown policy and the implementation of restrictions on community activities (IRCA) from the government which requires some people to be willing to lose their livelihood. Meanwhile, out of 100,000 people in Indonesia, 140 of them are at risk of being exposed to crime. The high crime rate is influenced by several factors such as education, less strict laws, high unemployment and inadequate wages. The purpose of this study was to determine the characteristics of crime and determine the factors that influence the occurrence of criminal acts in Central Sulawesi during the Covid-19 pandemic. This type of research is a type of descriptive qualitative research and descriptive quantitative. The data used in this study is secondary data from the Central Statistics Agency and the Central Sulawesi Regional Police. The research method used is multiple linear regression. The results of this study show that the characteristics of crime in Central Sulawesi during the pandemic, namely ordinary theft cases became the highest indicator in criminal cases, while theft in the family became the lowest indicator in criminal cases. In addition, it is known that the dominant criminal acts are carried out by men with self-employed and unemployed jobs, with the last education being high school or equivalent. Partially, the variable Number of Poor People has a significant effect on crime that occurs in Central Sulawesi and simultaneously or together the four variables, namely education, unemployment, Gross Regional Domestic Product (GRDP) and Number of Poor Population have an effect on the occurrence of crime in Central Sulawesi. The result of the coefficient of determination in this study was 79.99% it means that the four independent variables are able to explain the dependent variable of 79.99% and the remaining 20.01% are other variables that have not been used as variables in this study.
Factor Analysis for Increasing Reading Literacy in Indonesia Rizka Pitri; Ayu Sofia
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15898

Abstract

Low interest in reading is a problem for our nation that must be solved, because Indonesia to occupy second position from bottom in terms of literacy. Most of the provinces in Indonesia are at low literacy activity levels and none of the provinces are included in the high literacy activity level. The lack of interest in reading can be influenced by many factors. Access of supporting resource where people get literacy materials, such as libraries, bookstores, and mass media, how people to get the information technology, and media devices to access literacy materials are the factor that can be affect the interest of reading. Literacy is one of the important cultures for a country. That is because the culture is able to influence the intelligence and well-being of a country's life. So the study aims to see what factors affect to increasing the literacy reading in the provinces in Indonesia. This study uses k-means clustering before applying factor analysis. Based on k-means clustering, two clusters are formed and showed one of the cluster showed that the second cluster is the provinces that have the highest number of library’s facilities. In addition based on the analysis factor in each cluster, two factors were formed, namely the standard factor for reading literacy levels and supporting the facilities for reading literacy. It can be concluded that the way to increase reading literacy in two clusters of the area in Indonesia are by increasing the standard of reading literacy level and supporting the facilities for reading literacy.
Application of Negative Binomial Regression Analysis to Overcome the Overdispersion of Poisson Regression Model for Malnutrition Cases in Indonesia Yudi Setyawan; Kris Suryowati; Dita Octaviana
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15903

Abstract

Indonesia is one of the developing countries that is struggling to eradicate the malnutrition problem. Malnutrition that occurs over a long period of time can have an impact on the deaths of sufferers and decrease human quality of life. This study aims to model the case of malnutrition that occurred in Indonesia Provinces during 2015 and get the main factors that cause the malnutrition problem. Variables studied consist of Malnutrition (Y), Vitamin A consumption (X1), Exclusive breastfeeding (X2), Immunization (X3), Water quality (X4), Healthcare center (X5), and Poverty level (X6). Based on the Kolmogorov-Smirnov test, the results of malnutrition data in Indonesia Province in 2015 do not follow Poisson distribution because of overdispersion. The presence of overdispersion cases in the Poisson regression model will have an impact on the inappropriateness of inferences. An alternative model that accommodates this case is the negative binomial regression model. By using this model, factors that are considered influencing malnutrition cases in Indonesia provinces in 2015 are Immunization (X3), Water quality (X4), and Poverty level (X6).

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